Biological regulatory networks group

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Regulatory networks govern a wide range of biological processes. There has been considerable effort to investigate the function of these both experimentally and from a theoretical perspective. Despite the advance in development of experimental methods it remains difficult to quantitatively charactersise the system accurately. Since the exact details are not completely understood, models capturing qualitative features have proven a useful tool in this investigation. A popular class of models approximates the concentrations of interacting components by two possible states (active and inactive). These Boolean models (Kauffman, 1969) have been employed to describe a wide range of regulatory systems like the network governing the segment polarity development in fruitflies, the yeast cell cycle and the network that determines the cell-fate in flowers.

In this project we propose to study a real-world regulatory network using stochastic boolean dynamics. Most investigations of such networks with boolean models have employed synchronous updating schemes leading to deterministic outcomes. We will investigate the effects of stochastic updating on the dynamical behaviour of the system. In the light of the fact that biological processes take place at small concentrations of molecules the stochastic model is thought to capture essential characteristics that are missed in a deterministic approach.